Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • Large Language Models can Implement Policy Iteration

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models can Implement Policy Iteration

    Ethan Brooks, Logan Walls, Richard L Lewis, Satinder Singh p30349-30366 from Advances in Neural Information Processing Systems 36
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  • Large language models can learn and generalize steganographic chain-of-thought under process supervision

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large language models can learn and generalize steganographic chain-of-thought under process supervision

    ROBERT MC CARTHY, Joey SKAF, Luis Ibanez-Lissen, Vasil Georgiev, Connor Watts, Hannes Whittingham, Lorena Gonzalez-Manzano, Cameron Tice, Edward Young, Puria Radmard, David Lindner p31375-31410 from Advances in Neural Information Processing Systems 38
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  • Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

    Noah Hollmann, Samuel Müller, Frank Hutter p44753-44775 from Advances in Neural Information Processing Systems 36
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  • Large Language Models for Lossless Image Compression: Next-Pixel Prediction in Language Space is All You Need

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models for Lossless Image Compression: Next-Pixel Prediction in Language Space is All You Need

    Kecheng Chen, Pingping Zhang, Hui Liu, Jie Liu, Yibing Liu, Jiaxin Huang, Shiqi Wang, Hong Yan, Haoliang Li p174945-174966 from Advances in Neural Information Processing Systems 38
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  • Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.

    Eghbal Hosseini, Evelina Fedorenko p43918-43930 from Advances in Neural Information Processing Systems 36
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  • Large Language Models Miss the Multi-agent Mark

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Miss the Multi-agent Mark

    Emanuele La Malfa, Gabriele La Malfa, Samuele Marro, Jie Zhang, Elizabeth Black, Michael Luck, Philip Torr, Michael Wooldridge p154855-154873 from Advances in Neural Information Processing Systems 38
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  • Large Language Models Must Be Taught to Know What They Don’t Know

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Must Be Taught to Know What They Don’t Know

    Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Wilson p85932-85972 from Advances in Neural Information Processing Systems 37
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  • Large Language Models of Code Fail at Completing Code with Potential Bugs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models of Code Fail at Completing Code with Potential Bugs

    Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis p41386-41412 from Advances in Neural Information Processing Systems 36
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  • Large Language Models Play StarCraft II:Benchmarks and A Chain of Summarization Approach

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Play StarCraft II:Benchmarks and A Chain of Summarization Approach

    Weiyu Ma, Qirui Mi, Yongcheng Zeng, Xue Yan, Yuqiao Wu, Runji Lin, Haifeng Zhang, Jun Wang p133386-133442 from Advances in Neural Information Processing Systems 37
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  • Large Language Models Think Too Fast To Explore Effectively

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models Think Too Fast To Explore Effectively

    Lan Pan, Hanbo Xie, Robert Wilson p113582-113610 from Advances in Neural Information Processing Systems 38
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  • Large language models transition from integrating across position-yoked, exponential windows to structure-yoked, power-law windows

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large language models transition from integrating across position-yoked, exponential windows to structure-yoked, power-law windows

    David Skrill, Samuel Norman-Haignere p638-654 from Advances in Neural Information Processing Systems 36
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  • Large Language Models' Expert-level Global History Knowledge Benchmark (HiST-LLM)

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models' Expert-level Global History Knowledge Benchmark (HiST-LLM)

    Jakob Hauser, Daniel Kondor, Jenny Reddish, Majid Benam, Enrico Cioni, Federica Villa, James Bennett, Daniel Hoyer, Pieter Francois, Peter Turchin, R. Del Rio-Chanona p32336-32369 from Advances in Neural Information Processing Systems 37
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  • Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning

    Jiapu Wang, Kai Sun, Linhao Luo, Wei Wei, Yongli Hu, Alan Liew, Shirui Pan, Baocai Yin p8384-8410 from Advances in Neural Information Processing Systems 37
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  • Large Pre-trained time series models for cross-domain Time series analysis tasks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Pre-trained time series models for cross-domain Time series analysis tasks

    Harshavardhan Kamarthi, B. Prakash p56190-56214 from Advances in Neural Information Processing Systems 37
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  • Large Scale Transfer Learning for Tabular Data via Language Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Scale Transfer Learning for Tabular Data via Language Modeling

    Josh Gardner, Juan Perdomo, Ludwig Schmidt p45155-45205 from Advances in Neural Information Processing Systems 37
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  • Large Spatial Model: End-to-end Unposed Images to Semantic 3D

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Spatial Model: End-to-end Unposed Images to Semantic 3D

    Zhiwen Fan, Jian Zhang, Wenyan Cong, Peihao Wang, Renjie Li, Kairun Wen, Shijie Zhou, Achuta Kadambi, Zhangyang Wang, Danfei Xu, Boris Ivanovic, Marco Pavone, Yue Wang p40212-40229 from Advances in Neural Information Processing Systems 37
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  • Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization

    Yuhang Cai, Jingfeng Wu, Song Mei, Michael Lindsey, Peter Bartlett p71306-71351 from Advances in Neural Information Processing Systems 37
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  • Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression

    Jingfeng Wu, Pierre Marion, Peter Bartlett p115667-115707 from Advances in Neural Information Processing Systems 38
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  • Large-Batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large-Batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes

    Zeyue Xue, Jianming Liang, Guanglu Song, Zhuofan Zong, Liang Chen, Yu Liu, Ping Luo p18694-18706 from Advances in Neural Information Processing Systems 35
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  • Large-Scale Differentiable Causal Discovery of Factor Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large-Scale Differentiable Causal Discovery of Factor Graphs

    Romain Lopez, Jan-Christian Huetter, Jonathan Pritchard, Aviv Regev p19290-19303 from Advances in Neural Information Processing Systems 35
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  • Large-Scale Distributed Learning via Private On-Device LSH

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large-Scale Distributed Learning via Private On-Device LSH

    Tahseen Rabbani, Marco Bornstein, Furong Huang p16153-16171 from Advances in Neural Information Processing Systems 36
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  • Large-Scale Optimization of Partial AUC in a Range of False Positive Rates

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large-Scale Optimization of Partial AUC in a Range of False Positive Rates

    Yao Yao, Qihang Lin, Tianbao Yang p31239-31253 from Advances in Neural Information Processing Systems 35
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  • Large-Scale Retrieval for Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Large-Scale Retrieval for Reinforcement Learning

    Peter Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy Lillicrap p20092-20104 from Advances in Neural Information Processing Systems 35
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  • LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting

    Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann p75354-75371 from Advances in Neural Information Processing Systems 36
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